Advancing Towards a Marine Digital Twin Platform: Modeling the Mar Menor Coastal Lagoon Ecosystem in the South Western Mediterranean

TL;DR

This paper introduces a Marine Digital Twin Platform for the Mar Menor Lagoon, utilizing AI and integrated datasets to simulate ecosystem responses and support real-time marine management decisions.

Contribution

It presents a novel digital twin platform that models a coastal lagoon ecosystem using AI, integrating diverse data sources for real-time monitoring and decision support.

Findings

Successful integration of diverse datasets for ecosystem modeling

Real-time simulation capabilities demonstrated

Enhanced stakeholder engagement through modular design

Abstract

Coastal marine ecosystems face mounting pressures from anthropogenic activities and climate change, necessitating advanced monitoring and modeling approaches for effective management. This paper pioneers the development of a Marine Digital Twin Platform aimed at modeling the Mar Menor Coastal Lagoon Ecosystem in the Region of Murcia. The platform leverages Artificial Intelligence to emulate complex hydrological and ecological models, facilitating the simulation of what-if scenarios to predict ecosystem responses to various stressors. We integrate diverse datasets from public sources to construct a comprehensive digital representation of the lagoon's dynamics. The platform's modular design enables real-time stakeholder engagement and informed decision-making in marine management. Our work contributes to the ongoing discourse on advancing marine science through innovative digital twin technologies.